Descriptions

Design phase decisions based on diagnosability lead to lower system costs and, in turn, higher quality products by means of reducing maintenance time and increasing system reliability. A case for diagnosability is presented. Functions of diagnosability are expounded upon including life cycle costs, statistical analysis, and design criterion to emphasize the necessity of diagnosability analysis early in the design phase. A diagnosability prediction metric is developed for system modeling of component failure rates and unjustified removals. The metric emphasizes ambiguity of system component indications as well as system structure. The metric is evaluated using historical data from the bleed air control system (BACS) on the Boeing 737-300. Seven design changes are suggested based on improving system diagnosability by changing component functions, modifying indications, and adding or changing sensors. The resulting designs are compared via Boeing's life cycle cost mechanism, DEPCOST model, based on cost improvements. It is shown that system improvements based on this prediction technique will increase the quality of a product since increased diagnosability decreases life cycle costs.